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EMMCVPR
2007
Springer
15 years 3 months ago
Bayesian Inference for Layer Representation with Mixed Markov Random Field
Abstract. This paper presents a Bayesian inference algorithm for image layer representation [26], 2.1D sketch [6], with mixed Markov random field. 2.1D sketch is an very important...
Ru-Xin Gao, Tianfu Wu, Song Chun Zhu, Nong Sang
IWCM
2004
Springer
15 years 3 months ago
Bayesian Approaches to Motion-Based Image and Video Segmentation
We present a variational approach for segmenting the image plane into regions of piecewise parametric motion given two or more frames from an image sequence. Our model is based on ...
Daniel Cremers
CVPR
2008
IEEE
15 years 11 months ago
Generalised blurring mean-shift algorithms for nonparametric clustering
Gaussian blurring mean-shift (GBMS) is a nonparametric clustering algorithm, having a single bandwidth parameter that controls the number of clusters. The algorithm iteratively sh...
Miguel Á. Carreira-Perpiñán
ICMLA
2008
14 years 11 months ago
Probabilistic Exploitation of the Lucas and Kanade Smoothness Constraint
The basic idea of Lucas and Kanade is to constrain the local motion measurement by assuming a constant velocity within a spatial neighborhood. We reformulate this spatial constrai...
Volker Willert, Julian Eggert, Marc Toussaint, Edg...
ECCV
2004
Springer
15 years 11 months ago
Image and Video Segmentation by Anisotropic Kernel Mean Shift
Mean shift is a nonparametric estimator of density which has been applied to image and video segmentation. Traditional mean shift based segmentation uses a radially symmetric kerne...
Jue Wang, Bo Thiesson, Yingqing Xu, Michael F. Coh...